Department of Microbiology, University of Washington, Seattle, Washington, United States of America.
Department of Medicine, University of Washington, Seattle, Washington, United States of America.
PLoS Comput Biol. 2014 Jun 19;10(6):e1003673. doi: 10.1371/journal.pcbi.1003673. eCollection 2014 Jun.
Trends in HIV virulence have been monitored since the start of the AIDS pandemic, as studying HIV virulence informs our understanding of HIV epidemiology and pathogenesis. Here, we model changes in HIV virulence as a strictly evolutionary process, using set point viral load (SPVL) as a proxy, to make inferences about empirical SPVL trends from longitudinal HIV cohorts. We develop an agent-based epidemic model based on HIV viral load dynamics. The model contains functions for viral load and transmission, SPVL and disease progression, viral load trajectories in multiple stages of infection, and the heritability of SPVL across transmissions. We find that HIV virulence evolves to an intermediate level that balances infectiousness with longer infected lifespans, resulting in an optimal SPVL∼4.75 log10 viral RNA copies/mL. Adaptive viral evolution may explain observed HIV virulence trends: our model produces SPVL trends with magnitudes that are broadly similar to empirical trends. With regard to variation among studies in empirical SPVL trends, results from our model suggest that variation may be explained by the specific epidemic context, e.g. the mean SPVL of the founding lineage or the age of the epidemic; or improvements in HIV screening and diagnosis that results in sampling biases. We also use our model to examine trends in community viral load, a population-level measure of HIV viral load that is thought to reflect a population's overall transmission potential. We find that community viral load evolves in association with SPVL, in the absence of prevention programs such as antiretroviral therapy, and that the mean community viral load is not necessarily a strong predictor of HIV incidence.
自艾滋病大流行开始以来，人们一直在监测 HIV 毒力的变化趋势，因为研究 HIV 毒力可以帮助我们了解 HIV 的流行病学和发病机制。在这里，我们将 HIV 毒力的变化视为一个严格的进化过程，使用病毒载量设定点（SPVL）作为替代指标，根据纵向 HIV 队列推断经验性 SPVL 趋势。我们开发了一种基于 HIV 病毒载量动力学的基于代理的流行模型。该模型包含病毒载量和传播、SPVL 和疾病进展、感染多个阶段的病毒载量轨迹以及跨传播的 SPVL 遗传性的功能。我们发现，HIV 毒力进化到一个中间水平，在传染性和更长的感染寿命之间取得平衡，从而导致最佳 SPVL∼4.75 log10 病毒 RNA 拷贝/ml。适应性病毒进化可以解释观察到的 HIV 毒力趋势：我们的模型产生的 SPVL 趋势与经验趋势的幅度大致相似。关于经验性 SPVL 趋势的研究之间的差异，我们模型的结果表明，变异可能是由特定的流行环境引起的，例如创始谱系的平均 SPVL 或流行的年龄；或者 HIV 筛查和诊断的改进导致采样偏差。我们还使用我们的模型来研究社区病毒载量的趋势，这是一种反映人群总体传播潜力的人群水平的 HIV 病毒载量测量。我们发现，在没有抗逆转录病毒疗法等预防方案的情况下，社区病毒载量与 SPVL 一起进化，并且平均社区病毒载量不一定是 HIV 发病率的有力预测指标。
